The evolution of the deformation microstructure and local crystallographic orientations are investigated for 10, 30, 50, 80 pct cold rolled 316L austenitic stainless steel strips results related to overall macro-texture evolution. microstructures characterized by scanning electron microscopy (SEM), including backscatter diffraction (EBSD), transmission (TEM). macro-textures X-ray (XRD) measurem...

Predicting microstructure and (micro-)texture evolution during thermo-mechanical processing requires the combined simulation of plastic deformation recrystallization. Here, a approach based on coupling full-field dislocation density crystal plasticity model cellular automaton is presented. A regridding/remeshing procedure used to transfer data between deformed mesh large-strain regular grid aut...

A 2D cellular automaton model developed for the simulation of grain growth in hexagonal metals is presented here. It allows the direct use of experimental measurement as input data. Texture evolution of a titanium alloy and a zirconium alloy are simulated on the basis of simple hypothesis and compared with experimental evolution as well as the results from a 3D Monte Carlo model. Results from b...

This work is devoted to new computational models for image segmentation, image restoration and image decomposition. In particular, we partition an image into piecewise-constant regions using energy minimization and curve evolution approaches. Applications of denoising-segmentation in polar coordinates (motivated by impedance tomography) and of segmentation of brain images will be presented. Als...

Microstructure evolution, mechanical properties, formability, and texture development were determined for AA6111 samples processed by asymmetric rolling (ASR) with different roll friction, velocity, or diameters, conventional rolling (CR), and equal-channel-angular pressing (ECAP). Highly elongated or sheared grain structures were developed during ASR/CR and ECAP, respectively. ASR led to impro...

Abstract. In this paper, we propose a new model for image restoration and image decomposition into cartoon and texture, based on the total variation minimization of Rudin, Osher, and Fatemi [Phys. D, 60 (1992), pp. 259–268], and on oscillatory functions, which follows results of Meyer [Oscillating Patterns in Image Processing and Nonlinear Evolution Equations, Univ. Lecture Ser. 22, AMS, Provid...

This paper proposes a novel content-based music genre classification method using temporal information and support vector machine. By processing of texture window statistics and delta computation, temporal information is incorporated to capture the time-varying behavior of music. 7 different temporal evolution descriptors applied in texture window are introduced in this paper, i.e., mean, stand...

We present a new algorithm for segmenting a scene consisting of multiple moving dynamic textures. We model the spatial statistics of a dynamic texture with a set of second order Ising descriptors whose temporal evolution of is governed by an AutoRegressive eXogenous (ARX) model. Given this model, we cast the dynamic texture segmentation problem in a variational framework in which we minimize th...

In this paper, we propose a novel approach for texture analysis based on artificial crawler model. Our method assumes that each agent can interact with the environment and each other. The evolution process converges to an equilibrium state according to the set of rules. For each textured image, the feature vector is composed by signatures of the live agents curve at each time. Experimental resu...

The automatic synthesis of procedural textures for 3D surfaces using genetic programming is investigated. Genetic algorithms employ a search strategy inspired by Darwinian natural evolution. Genetic programming uses genetic algorithms on tree structures, which are interpretable as computer programs or mathematical formulae. We use a texture generation language as a target language for genetic p...